1. Field of the Invention
This invention relates generally to computer integrated manufacturing systems and methods. More particularly this invention relates to systems and methods of a computer integrated manufacturing system that performs capacity planning to allocate usage of manufacturing sites, the manufacturing areas within the manufacturing sites, and the equipment within the manufacturing area of a manufacturing enterprise.
2. Description of Related Art
In manufacturing enterprises such as semiconductor fabrication companies commonly referred to as silicon foundries, there are numerous factories at various locations that are capable of fabricating differing types of product. The manufacturing enterprises are classified as having heterogeneous production lines. Each of the factories may have multiple fabrication lines, employing different sets of processing equipment. Currently the acquisition and distribution of raw material, component parts, and work-in-process of the product (the supply chain) of most fabrication lines is highly automated and controlled by computer integrated manufacturing systems (CIM). The CIM system receives dispatch scheduling information regarding the product to be manufactured from an order management system. From the dispatch scheduling information, the CIM system schedules the necessary processing equipment and acquisition and distribution of the raw materials and component parts. The CIM system then starts the manufacturing process and provides monitoring of the processing equipment through manufacturing execution systems within the enterprise. Further, the CIM system provides monitoring of the testing and verification to insure the quality of the product during fabrication and upon completion of fabrication. The CIM system, additionally, controls the location and quantities of storage of the product in inventory and processing of the product for shipment to a customer.
The CIM system employs various software tools for planning capacity of the manufacturing elements of the manufacturing enterprise. These elements are the various factories or sites, the manufacturing areas (production lines or equipment pools) within the factories, and the fabrication, handling, and testing equipment of the manufacturing areas. These software tools normally determine optimization at a local level, for instance between manufacturing areas or among the equipment of the manufacturing area. These software tools do not provide for balancing of the utilization over the entire set of heterogeneous production lines or the whole supply chain for an manufacturing enterprise.
Refer now to FIG. 1 for more discussion of the structure of an automated manufacturing enterprise. The manufacturing enterprise has a component part procurement unit 5 and a raw material procurement unit 10 which communicates with vendors or subcontractors to acquire the necessary component parts and raw materials for the fabrication of product lots within the enterprise. The component part procurement unit 5 and raw material procurement unit 10 communicate the technical requirements of the component parts and raw material, the negotiated pricing, and required delivery scheduling. The part procurement unit 5 and the raw material procurement unit 10 are respectively connected to the manufacturing execution systems (MES) 35 and 40. The manufacturing execution systems 35 and 40 are connected to the network 65 and thus is in communication with to the computer integrated manufacturing system (CIM) system 90. The CIM system provides the necessary scheduling for the product lots and dispatches the orders for procurement of necessary raw materials and component parts according to the scheduling.
The enterprise has a number of factories or fabrication sites 15a, . . . , 15n which in turn have at least one fabrication area, with each fabrication area having the appropriate equipment for fabrication of the product lots. The fabrication sites 15a, . . ., 15n are connected to the MES systems 45a, . . . , 45n. The MES systems 45a, . . . , 45n are connected to the sensors and control circuits of the equipment within each of the fabrication sites 15a, . . . , 15n to determine the status of each piece of manufacturing equipment and control the operation of each piece of the equipment. Further, the MES systems 45a, . . . , 45n provide the local scheduling and dispatch of the product lots to the appropriate equipment to maximize utilization of the manufacturing equipment and expedite processing of the product lots through the fabrication sites 15a, . . . , 15n. The MES systems 45a, . . . , 45n are connected to the network 65 and thus are in communication with the CIM system 90. The CIM system 90 provides the scheduling of the product lots for fabrication and dispatches the product lots to one or the appropriate fabrication sites 15a, . . . , 15n for fabrication. The MES systems 45a, . . . 45n of the fabrication sites 15a, . . . , 15n are in communication with the MES systems 35 and 40 to coordinate delivery of the necessary raw materials to the correct fabrication site 15a, . . . , 15n to insure that the fabrication of the product lots occurs according to the schedule.
At the completion of each procedure of a fabrication process, the product is tested and verified that it meets the requirements of the design of the product. Additionally, at the completion of the total fabrication the product the product is again tested to verify that the product complies with the specifications established for the product. The product testing unit 20 provides the necessary test and verification equipment in either separate test areas within the enterprise or integrated within the fabrication sites 15a, . . . , 15n. The product testing unit 20 is connected to an MES system 50 to provide the scheduling of the testing equipment necessary for the testing and verification processing of the product lots during fabrication and at the completion of the fabrication. The MES system 50 is connected to the network and thus is in communication with the CIM system 90 and the fabrication sites 15a, . . . , 15n. The MES system 50 receives the scheduling to the product lots and the required test parameters and programs necessary to coordinate the testing and verification and to configure the testing equipment for operation.
Any of the procured raw material or component parts that arrive prior to consumption rather than just in time for consumption must be stored in an warehouse and inventoried. Further, during any delays between procedures or stages in the process of fabrication of the work-in-process product maybe placed in a storage area and must be inventoried. Additionally, upon completion of the product and prior to scheduled shipment the product must be placed in a warehouse for storage prior to shipment. The inventory control unit 25 administers the inventory of component parts, raw material, work-in-process product, and completed product. The inventory control unit 25 is connected to the MES system 55. The MES system 55 is connected to the network 65 to communicate with the CIM system 90. The MES system 55 identifies the placement of the component parts, raw material, work-in-process product, and completed product within the warehouse and provides the scheduling for entry and exit of the component parts, raw material, work-in-process product, and completed product from the warehousing based on the product lot scheduling developed by the CIM system 90.
Upon completion of the fabrication of the product, the product is either placed in inventory awaiting scheduled shipment or is sent directly to a shipping unit 30. The shipping unit 30 provides the materials handling services such that the product is transferred appropriately to a customer. The shipping unit 30 is connected to the MES system 60 and is communication with the CIM system 90 which the provides the necessary scheduling for the shipment of the product lots as appropriate.
The order management system 70 controls the marketing and sales database 75. A marketing and sales department enters orders to the order management system 70 when a customer requests fabrication of a product. Further, the marketing and sales department is in contact with the established and potential customers of the manufacturing enterprise to provide an estimate of the product lots that maybe fabricated. This estimate, the current orders for fabrication of product lots, and the history of previously fabricated product lots are placed in the marketing and sales database 75. A fabrication forecast is a planned or predicted schedule of the product lots developed from the estimate of product lots to be fabricated, the current orders for fabrication of product lots, and the history of previously fabricated product lots. This schedule is transferred to the CIM system 90. Further, the industrial engineering system 80 is in communication with the CIM system 90 through the network 65 to provide the identifications and location of the types of the equipment available for fabrication of the planned product lots.
The CIM system 90 receives the planned schedule, the equipment information, and from the process database 95 the process description for each product scheduled to be fabricated. From this information the CIM system 90 creates a supply chain allocation and utilization plan for each product lot to the fabrication sites 15a, . . . , 15n. The distribution of the product lots is balanced to insure that the fabrication sites 15a, . . . , 15n are appropriately utilized. The CIM system 90 then allocates the equipment within the fabrication sites 15a, . . . , 15n. The utilization of the equipment is then balanced by shifting product lots to other equipment or by sub-contracting the services to outside suppliers. The planned schedule is transmitted to the MES systems 35, 40, 45a, . . . , 45n, 50, 55, and 60 to act as a planning vehicle for allocation of the product lots prior to the actual dispatching of the product lots from actual orders.
The method for the development of the supply chain allocation and utilization plan is shown in FIG. 2. The fabrication sites 15a, . . . , 15n of FIG. 1 maybe divided into multiple fabrication units with each unit being divided into multiple fabrication areas. Each fabrication area is structured to contain specific equipment or associated types of equipment necessary for processing the lots of product. The CIM system 90 requests and receives a fabrication forecast 100 for an extended period of time (i.e. 8 weeks) from the order management system 75. The CIM system 90 retrieves the product process description from the process database 95 of FIG. 1 and requests the equipment requirements listing from the industrial engineering system 80 of FIG. 1 to provide a location 110 listing describing the fabrication units containing the necessary equipment for the fabrication each of the product lots. The CIM System 90 then allocates (Box 105) the product lots to the appropriate fabrication units. The CIM system 90 then balances (Box 115) the distribution of the product lots over the fabrication units to insure appropriate utilization. The CIM system 90 then retrieves the product process description 125 from the process database 95 of FIG. 1 and the CIM system then allocates (Box 120) the product lots to the appropriate equipment sites within the fabrication unit. The CIM system 90 then balances (Box 130) the distribution of the product lots over the equipment sites of the fabrication area and provides a report 135 describing the planned equipment utilization and any suggestions for contracting with sub-contractors for performing the appropriate processing of the product lots.
U.S. Pat. No. 6,606,529 (Crowder, Jr., et al.) describes a device and method for the real time optimization of scheduling for manufacturing and information transfer systems. The method generates an optimal solution to a scheduling problem by employing a filtering algorithm to schedule minimally-conflicting events. The remaining unscheduled events are partitioned into non-interactive sub-sets. Following partitioning, artificial intelligence is used to select one of a plurality of algorithms which is employed to provide an optimal scheduling solution for each sub-set of scheduling requests. The purpose of artificial intelligence is to recognize certain characteristics in request data comprising each sub-set of event scheduling requests and select an algorithm which is optimal for scheduling each particular sub-set.
U.S. Pat. No. 6,006,192 (Cheng, et al.) details a decision-making method suitable for production planning in an uncertain demand environment. The method combines an implosion technology with a scenario-based analysis, thus manifesting, a customization capability which preserves the advantages and benefits of each of its subsumed aspects.
U.S. Pat. No. 5,953,707 (Huang, et al.) describes a decision support system for the management of an agile supply chain that provides an architecture including a server side and a client side. A servers includes a decision support system database that interfaces with a model engine that performs analysis of the data to support planning decisions and a server manager that coordinates requests for service and information. The client includes decision frames that present the various view points available in the system to the users. A frame manager coordinates the requests from decision support frames to access the needed data and models. The decision support frames provide a view into the supply chain and integrate analytical models responsive to the view point of a business process such as demand management. The frames include a supply management frame, a demand management frame, a vendor managed replenishment frame, a Planning, Sales and Inventory planning frame, and a distribution network design frame.
U.S. Pat. No. 5,787,283 (Chin, et al.) teaches a framework suitable for manufacturing logistics decision support. An object-oriented technology framework which defines objects representing manufacturing logistics problems; transforms a subject of the above objects into representations commonly used in a mathematical solver, wherein the representations in the solver have predefined relationships based on their properties. The behavior of the framework is modified upon selective changes in the objects to develop a new manufacturing logistics decision support application.
U.S. Pat. Nos. 5,721,686 and 5,559,710 (Shahraray, et al.) teach an improved system and method for scheduling a plurality of orders into a factory for processing by one or more of a plurality of machines based on the use of a continuity Index job release strategy. The system and method is particularly addressed to the enhancement of such a job release strategy by introduction of factory profile and priority criteria and an algorithm for automatic determination of an optimum job release point based on such criteria.
U.S. Pat. No. 5,369,570 (Parad) describes a method for continuous real-time management of heterogeneous interdependent resources. The method uses multiple distributed resource engines to maintain timely and precise schedules, and action controls, and identifying and responding to rapidly changing conditions in accord with predetermined requirements, relationships, and constraints. Each resource engine continuously adjusts schedules in response to changing status, resource requirements, relationships and constraints. Each action control maintains an ordered list of conditions requiring action, determines the best action in each case, and generates appropriate responses.
U.S. Pat. No. 6,456,996 (Crawford, Jr., et al) describes a method and system for solving constrained optimization problems. An initial abstract solution represents a prioritized set of decisions. The abstract solution is used as the basis for building a concrete solution. The concrete solution is analyzed to determine one or more local moves that represent a re-prioritization of the abstract solution. After a local moves is made, the process begins again with a new abstract solution that is closer to an optimal solution. This process continues interactively until an optimal solution is reached or approached. The prioritized set of decisions can be implemented as a priority vector or a priority graph.
U.S. Pat. No. 6,397,192 (Notani, et al.) teaches a computer implemented method for workflow synchronization is provided. The first step comprises initializing the execution of a plurality of workflows. The next step is providing synchronization logic in at least one of the plurality of workflows. In the third step the execution of a workflow is paused until the synchronization logic is complete. In the final step the execution of the plurality of workflows continues.
U.S. Pat. No. 5,946,212 (Bermon, et al.) illustrates a computer implemented method that provides accurate capacity planning for manufacturing environments comprising parallel, unrelated tools that can process the same operations at different rates and with preferences for the sequence in which those tools are selected to accommodate the workload. The method reliably determines, precisely, the gating tools among sets of parallel, unrelated tools in a complex manufacturing environment in which different tools can perform the same or similar sets of operations, generally, at different rates. The primary, secondary, etc. tool groups in each cascade set are explicitly kept track of in order to enable the correct penalty function to be associated with the appropriate tool group.
G. R. Bitran and D. Tirupati, “Planning and Scheduling for Epitaxial Wafer Production Facilities,” Operations Research, Vol. 36, No. 1, 34-49, 1988 describes. models used for scheduling jobs for epitaxial growth on semiconductor substrates in the reactors. This stage was a bottleneck operation of a semiconductor wafer processor. A facility with different product groups is consider and several heuristics two criteria are proposed. A non-linear programming problem is formulated to assign reactors to product groups to obtain homogeneous product mix. The significance of this model is due to the fact that homogeneous product set enables use of a simpler heuristic and reduces the complexity of the scheduling system. The non-linear program can be interpreted as an attempt to identify, within the facility, smaller independent shops with homogeneous product groups.